Specialized in Long Term Care, Medical-surgical and Nephrology. Used SQL queries for inventory management to determine when new orders needed to be placed, for what parts to replenish, which parts should be quoted, and find the lead time needed to meet production. My ultimate goal is to get a job that fits my main interests which are (from most important to least): statistical analysis, making and testing statistical models, speculative investing (preferably with options), coding ( python preferably). Committed to excellence in the delivery of healthcare services and improving quality of life and wellbeing. Completion of MFE coursework CFA, Work closely with the business, Market Risk, Finance/PVG and other control functions with respect to compensating controls of the models and communication of validation outcome, In depth understanding of financial mathematics including stochastic differential equations, probability theory, statistical analysis, interest rates and credit risk modeling, Quantitative modelling and/or validation experience in IM/VaR models is preferred, Strong and diversified quantitative skills, Working knowledge of the main asset classes available on the market(equities, fixed-income securities, options), Working knowledge of derivative financial instruments and the numerical methods used to price them, Working knowledge of stochastic processes and stochastic calculus/integration, Working knowledge of optimization techniques, regression techniques and Monte Carlo simulation, Ability to understand and communicate clearly and effectively at all levels, Ability to learn and adapt in an unexplored field, if necessary, Review the underlying assumptions, theory,conceptual soundness, derivationof the models, empirical evidence, calibration, implementation and limitations of the model being validated, Perform independent testing to identify/quantify model risks associated with the models being validated, Work closely with the business, other stakeholders other control functions with respect to compensating controls of the models and communication of validation outcomes, Masters or PhD in quantitative fields such as computational finance, mathematics, statistics or equivalent, In depth understanding of statistical concepts and model development & validation processes, 3 to 5 years experience in financial services industry building or validating models, Familiar with SR11-07 and related requirements on model risk, Member of the VaR backtesting team based in NY, Supporting the daily process around backtesting setup and maintenance, execution and exception analysis liaising with Middle Office, Finance, Enterprise Capital Management and Market Risk Management, Working with the VaR model development team to understand our VaR model implementation and assess the impact of model limitations on our backtesting results, Supporting process improvement and automation initiatives, Assisting in the production and presentation of reporting packages and analysis for senior management, governing committees and regulatory bodies, Defining and prototyping the toolsets needed to run and analyse the FRTB Backtesting and P&L attribution tests, Masters degree in quantitative fields such as mathematics, statistics, physics or equivalent, 3+ years of work experience in Market Risk or Market Risk Analytics, Strong knowledge of Var modeling techniques, Experience in investigation of back-testing exceptions and data analysis, Ability to multitask with strong time management skills, Perform PPNR modeling, PPNR back-testing and stress testing reconciliation, Responsible for mapping and populating DFAST result templates, Assist in stress testing aggregation and capital projection, Partner with business lines to ensure reasonableness of stress testing data, assumption and results, Perform ad-hoc capital analyzes to support capital decision making process, Maintain stress testing documentation and provide support for model validation, audit and supervisory reviews, 3+ years ALM modeling or relevant experience, Highly motivated with strong analytical skills, High level computer proficiency (MS Excel, Access, SQL, AQT, PowerPoint), Understand and be able to use statistic regression to support stress test, Ability to handle multiple tasks and work well in time-sensitive environment, Communicate clearly and concisely in verbal & written form, 5+ years in an application development role, Object-oriented application development experience, SQL development (writing queries, analysis of existing SQL queries), Excellent communications skills, both oral and written, Testing (including unit tests) and reconciliation of results, Degree in a technical field (computer science, financial mathematics, engineering, physics), Experience with analytic finance, especially within a large financial institution, C++ (other projects in the group are developed in C++ and this candidate may get opportunities to work on those projects), SAS programming (just to understand logic of existing SAS scripts), Excel/VBA (just to understand logic of existing Excel spreadsheets), Experience writing mathematical algorithms for scientific computing, Conduct detailed analyses of operational loss data; Develop scripts/code to automate data reviews, trend analyses, and outlier detection, Challenging current data analysis and data collection assumptions as needed, Developing code to conduct data reviews and independent testing of collected data, Writing technical reports for distribution and presentation to senior management, model developers, audit and bank regulators, Masters degree in a quantitative field with 2+ years of quantitative modeling experience or PhD in a quantitative field, Knowledge of banking products and services, Experiences with a statistical analysis package such as SAS or R, Ability to interact with model implementation team, Variance analysis and reporting of monthly and quarterly changes in wholesale capital, Responsible for investigating and explaining key drivers, Work closely together with the capital line of business teams to stay up to date about expected commercial portfolio changes, Involved in setting up requirements for potential model changes, Responsible for reviewing model changes. Solid knowledge of pricing model on equity, fixed income and options, as well as stochastic process, regression analysis, and Monte Carlo simulation. Python Here's how python is used on quantitative analyst resumes: Developed a statistical analysis tool in Python to optimize Gas emergency response staffing requirements. Built the virtual optimized portfolio to analysis the real portfolio (cash desk)s diversification risk and tail risk. Here are a few tweaks that could improve the score of this resume: Since 2005, LiveCareers team of career coaches, certified resume writers, and savvy technologists have been developing career tools that have helped over 10 million users build stronger resumes, write more persuasive cover letters, and develop better interview skills. Common examples include (1) the pricing of derivative securities such as options, and (2) risk management, especially as it relates to portfolio management applications. Providing sell-side advisory on a $180mm acquisition through creating earnings, valuation and industry models including. Performed time series analysis on stock return, fitting ARIMA model and conducting the residual analysis. Used SQL queries in Access to maintain cost accounting records of all parts in the division and generate financial metrics for quantitative analysis. Engaged in increasingly complex projects that required collaboration with multiple business units, such as traders, information technology experts, corporate attorneys, and fellow analysts. Quantitative Financial Analyst Resume, Curriculum Vitae Ama De Llaves, Professional Analysis Essay Writer Websites Uk, Short Paragraph My Favorite Game Football Class 5, Sap Quality Assurance Resume, Resume For A Scholarship Application, Once you have a clear explanation of your thesis statement, it's time to review the assignment criteria and choose an argumentative structure. Negotiated blanket orders and managed contracts, led inventory reduction team & on-time delivery program. Guide the recruiter to the conclusion that you are the best candidate for the quantitative finance analyst job. Designed daily, weekly, and monthly performance reports of both client and in-house funds and delivered reports regularly via website reporting, email distribution, conference calls, and in-person meetings. Privacy policy Similar Roles. Financial analysts often work on financial models to improve a company's financials. Performing due diligence on hedge fund managers through face to face meetings, conference calls and other tools suchas Cambridge and Pertrac database. Was responsible for data analysis, models execution, and outcome analysis during several ccar cycles. Priced financial derivatives in the CGMY model using numerical approaches such as the trapezoidal and Simpson's rules. Calculated and optimized capital reserve for Barcap's equity vanilla book based on new FSAS rule. Objective : Quantitative Analyst successfully drove future business strategies to positively impact sales by fetching data using SQL and QTRAX and performing data munging, data transformation, and data analyses to create visual reports in Tableau. A financial analyst resume needs to bring out technical and quantitative skills. * Analyzes and develops new model frameworks by supporting the line of business. Interpreted results of these models, and presented them to senior management. Consistently assumes responsibility to complete projects within time and financial constraints, Skills : Neural Networks, Logistics Regression, Support Vector Machine, Bayesian Networks, Decision Trees, And Clustering. Quantitative Analyst - Model Risk Management, Vice President - Hybrid. Found the most appropriate values of parameters including dampening factor implemented in the CGMY model. SAS, R), C++, VBA, LaTex, Working on the model development of revenue forecasting for GBAM in the context of CCAR including, In depth knowledge of statistics skills: good understanding of statistical models is needed, PhD in Statistics is a definite plus, and a specialisation in econometrics and time-series are highly desirable, The projection engine is currently done in R, so experience coding in R would be a plus, Good communication skills (both written and verbal): we will need to defend the models in front of model risk management (MRM) and explain them in an easy way to the business, Proactively monitor and remediate any market data issues that is used in production risk measurement and reporting, Ensure the completeness, validity, and accuracy of market data on a daily basis, Work with business data users to define the use of data within various risk systems. The Financial Analyst job description template also elaborates on providing financial strategy decisions. 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